The present invention relates to automotive diagnostics, and more specifically, to a system and method of predicting automotive problems or failure based on a collection of historical information.
Automotive repair is, for the most part, inevitable. If driven long enough, most automobiles will require at least some form of routine maintenance and repair. Although repairs are almost certain, it is unknown as to when the vehicle will fail, and therefore, automotive failure usually comes as a surprise. Furthermore, the average vehicle owner does not know what those failures are likely to be or what the related cost of repair would entail.
The difficulty in predicting diagnostic events for a vehicle stem from the fact that different vehicles exhibit different vulnerabilities. Therefore, a particular component may be susceptible to failure in a particular vehicle, and not as susceptible to failure in another model of vehicle. Furthermore, that same component may have a different susceptibility of failure from one model year to the next in the same model of vehicle. Thus, there is not a universal template or formula that can be applied to all vehicles for predicting when failure is likely to occur.
To the average automobile owner, there is a considerable amount of uncertainty associated with automotive diagnostics and repair. Automobiles are complex electro-mechanical devices, and as such, when a problem associated with the operation of the automobile arises, it may be well beyond the skill of the ordinary automobile owner to identify the problem and know how to perform the related fix. Thus, automobile owners have been relying on automotive professionals, such as a repair shop or dealership, to assist in the diagnosis and repair of their automobiles.
Although automotive professionals may be helpful in diagnosing and repairing an automotive problem, there is a certain level of distrust consumers have associated with automotive professionals. In some instances, the automotive professionals may leverage their experience and knowledge when dealing with the consumer to drive up the cost or to encourage the consumer to make repairs which may not be absolutely necessary. Therefore, consumers tend to feel as if they have been taken advantage of when they visit automotive professionals. That feeling is compounded by the fact that costs associated with having an automotive professional service your vehicle tends to be very high.
Aside from automotive professionals, oftentimes the best available information is from someone who currently owns or previously owned the same year, make, and model of the vehicle under consideration. That person can describe their experience with the vehicle, including the maintenance history or any repairs that performed on the vehicle, and when those repairs took place (i.e., at 50,000 miles, etc.).
Although the information received from the experienced individual may provide some measure of assistance in gauging the diagnostic future of a particular vehicle, the information provided by the experienced individual may not be representative of a pattern of failure. In this regard, there is a likelihood that the failures, or lack thereof, identified by the experienced individual may not be attributable to a reliable pattern, but instead are simply anecdotal events which may provide very little basis for reliability.
As such, there is a need in the art for a reliable and comprehensive predictive diagnostic system and method which provides a predictive diagnostic summary for a vehicle under consideration, wherein the predictive diagnostic summary is compiled from a historical database of similar vehicles.